Study of Low Terahertz Radar Signal Backscattering for Surface Identification.

This study explores the scattering of signals within the mm and low Terahertz frequency range, represented by frequencies 79 GHz, 150 GHz, 300 GHz, and 670 GHz, from surfaces with different roughness, to demonstrate advantages of low THz radar for surface discrimination for automotive sensing. The responses of four test surfaces of different roughness were measured and their normalized radar cross sections were estimated as a function of grazing angle and polarization. The Fraunhofer criterion was used as a guideline for determining the type of backscattering (specular and diffuse).

Experimental Evaluation of 79 and 300 GHz Radar Performance in Fire Environments.

This paper presents an experimental study of the propagation of mm-wave/low-THz signals in the frequency ranges of 79 and 300 GHz through fire. Radar performance was investigated in various real scenarios, including fire with strong flame, dense smoke and water vapour. A stereo video camera and a LIDAR were used as a comparison with other common types of sensors.

Underwater Optical Imaging for Automotive Wading.

An underwater imaging system was investigated for automotive use in highly scattered underwater environments. The purpose of the system is the driver's information about hidden obstacles, such as stones, driftwood, open sewer hatches. A comparison of various underwater vision methods was presented by the way they are implemented, the range reached, and the cost of implementation.

Automotive System for Remote Surface Classification.

In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor.

FPGA design for dual-spectrum Visual Scene Preparation in retinal prosthesis.

A method of Visual Scene Preparation for the patients suffering Retinitis Pigmentosa is implemented in hardware for the first time. The scene is captured with two cameras, one visible spectrum and one infra-red, in order to distinguish between the live and non-live objects. The live objects are subsequently emphasized in the output image, thus helping a patient to see the most significant detail with the healthy part of the retina.